To analyze heterogeneous substances or mixtures of substances, such as powders, pastes, suspensions, or solids, a variety of different measurement methods are used, wherein each of which aims at one or more specific properties. A powder can be examined by light scattering studies in order to determine the particle size distribution. The chemical properties of a material can be determined with high accuracy both in volume and in the surface composition. Analogously, electrical and magnetic properties of the material or material mixture can be measured. The time consuming and equipment expense of these measurement methods are very different. However, not all of the methods are suitable for a sufficiently rapid or real-time process control.
Methods for analyzing powder and precise material analysis are usually complex, costly and time-consuming processes. Especially, with heterogeneous materials such as powders, pastes, suspensions, solids, heterogeneous mixtures, the correlation between physical and chemical properties and behavior during the manufacturing process is complex and difficult to analyze. Therefore, usually empirical knowledge is used. In general, it is not possible to conclude from the collective properties of a large particle number, such as a bulk material or a powder, the properties of individual particles, and vice versa.
Even with an accurate chemical analysis of a very large number of particles and a high-precision determination of particle size distribution and particle shapes, it is difficult to conclude about process relevant data, such as free-flowing properties, clumping tendency or the apparent density. The complexity of bulk material or powders complicates quality assurance in a production processes.
In industrially relevant processes, both the statistical distribution of particle sizes and particle shapes, as well as the chemical composition of the particles in the bulk and on the surface, is important. In powder mixtures, the degree of complexity is correspondingly higher.
For production, it may be necessary to accurately detect whether a change in the composition of the starting materials being fed through. Any change of the material batch, the material source, or the supplier increases the risk that established and empirically controlled processes become unstable. Often, supplier side changes of the material composition are not communicated since the change is considered to be of little relevance. Errors in the production process are often complex and subjected to a causal chain. Later on, one can therefore hardly prove that a certain defective raw material is the cause of an error.
The translation DE 600 23 005 T2 of the European patent EP 1 194 762 B1 discloses a system, apparatus and method for a multiple logging of a combination of both chemical and physical characteristics of a particular analyte in a given environment to generate a unique signature. In addition, an unknown analyte can be detected and identified by comparison of its unknown signature with a stored output signature of a known analyte or a mixture of substances. A measurement data set is evaluated by algorithms. The algorithm can optimize the feature selection and the sensor selection. The algorithm may be a neural network which is trained by correcting the wrong or undesirable outputs on the basis of predetermined criteria in a collection of data. Amongst others, related correlation variables are transformed into a smaller number of uncorrelated variables (principal component analysis, PCA). The aim of the PCA is to reduce the dimensionality of the data set. Applications include control of material quality, labor protection or monitoring of food and agricultural products. However, the method disclosed does not analyze the material in terms of macroscopic material properties, such as particle size, size distribution, state, rheological properties and mixing ratio of powdery and heterogeneous materials. Also, the disclosed automated material quality control is not operated continuously or integrated into existing production processes. Further, the signature of a substance is not to process- or machine-correlated.
The translation DE 694 17 519 T2 of the European patent application EP 0 606 121 B1 discloses a device for automatic quality inspection of selected metrics of powdery products. A variety of test equipment and data station computers capture these measurements parallel to subsets of the powder. Measurement values include the particle size, the bulk density or the degree of polymerization. The measurement data obtained are combined in a central data processing and compared with the quality standards. Also, impurities are determined and recorded quantitatively. The selection of the measured values, however, is not automated. There is no algorithm provided for determining a reduced or minimal set of measurement values that are sufficient for a unique sample determination. Furthermore, the material subsets to be measured are supplied in containers with robotic arms according to labels on the containers to an appropriate measuring device. Also, during the measurements and their evaluation, environmental conditions are not considered.
The German patent application DE 33 08 998 A1 discloses a device specially designed for the measurement of dispersive properties of powders or aerosols. Chemical parameters or values are not determined. Powders are no identified. A digital data acquisition and data analysis is not described.
International patent application WO 99/61902 A1 discloses a method and a system for identifying analytes and to distinguish them from other analytes. Analytes mean here carried odors, especially in vapor or liquids. In certain cases, a statistical metric is used. A variety of sensors is exposed to different odors and generate according to electrical responses, which are represented as a vector in a d-dimensional space. A statistical metric is optimized in a central computer with respect to selectivity between first and second odor as well as the smallest possible number of detectors. This is implemented mathematically by determining the project axis on a low-dimensional subspace as possible of the d-dimensional space, which has by an optimal separation of records of two different odors. Described sensor types include, inter alia, acoustic, chemical and micro-opto-electro-mechanical devices. The response of all sensors in combination creates a “fingerprint” that can be used to identify the analytes. The examination methods are based on chemical properties, however, not physical, in particular rheological properties. Although, the reduction of the set of sensors serves to achieve faster and more efficient measurements, but no integration into a production process or real time production support is disclosed. The “fingerprint” is also not used in tamper-proof markings of a substance. The signature of a substance is also not process- or machine-correlated.
The U.S. Pat. No. 5,074,158 discloses an apparatus for continuous examination of a powder which is passed through a tube of a production plant. The test result is obtained by optical detection, displayed as an image on a monitor and analyzed by an image analyzer. An identification of the powder is not provided. Furthermore, the measured data sets are not associated or evaluated by computerized algorithms.